Within the past decade, technological advances in positron emission tomography (PET) imaging have provided information previously unobtainable about the neurochemical factors involved in normal aging as well as their role in neurological diseases of the elderly including Alzheimer's Disease. Despite these advances, PET imaging is limited by the need to correct for effects of partial volume averaging. Consideration of these effects is key; without it, alterations in brain metabolic rates or receptor binding may be interpreted as intrinsic changes in brain chemistry when, in fact, they arise due to brain atrophy.This project is a multidisciplinary approach to the development, validation and implementation of an analytic model for whole brain correction of partial volume effects in PET imaging. The goal of this project is to apply the model to estimate regional brain radioactivity concentrations in gray matter tissue. Validation methods are described using computer generated PET images derived from tissue segmented MRI images, realistic agarose gel brain phantoms and PET in ex vivo measurements in baboons. Following validation the method will be applied to measurements of regional brain glucose metabolic rate using F-18 fluorodeoxyglucose and regional brain mu opiate receptors using C-11 carfentanil. The impact of the partial volume correction method on measurements of brain glucose metabolism and mu opiate receptors is a function of age in healthy human subjects and in patients with Alzheimer's Disease. By eliminating the confounding variable of partial volume effect in these studies, the result is more accurate quantification of brain glucose metabolism and mu opiate receptors, which we hope will lead to the discovery of new patterns of change in normal aging and Alzheimer's Disease.